Senior Manager, Data & Analytics

Career Category Information Systems Job Description Join Amgen’s Mission of Serving Patients At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Senior Manager, Data & Analytics What you will do Let’s do this. Let’s change the world. In this vital role, you will serve as the business engagement and technical delivery lead for prioritized Enterprise Data Strategy & Engineering (EDSE) initiatives. You will lead assigned initiatives from discovery through delivery, adoption, and value realization—translating business priorities into scalable data, analytics, reporting, and AI-enabled solutions. You will partner with Business Owners, EDSE Platform, Engineering, Governance, Architecture, Agile/PMO, and Amgen GCC Engineering teams to define outcomes, shape roadmaps and delivery plans, manage dependencies, and deliver measurable business value. Operating at the intersection of business strategy and technology, you will co-lead with Business Owners and Technical Product Owners/engineering leads to deliver incremental value through an outcome-based roadmap and prioritized backlog. The successful candidate will bring the technical depth to lead solutions using Databricks, AWS, Power BI, and other EDSE strategic platforms through solution design, build, testing, release, adoption, and ongoing enhancement. The ideal candidate is an outcome-oriented leader with life sciences experience, strong business acumen, and credible data and analytics delivery expertise. Responsibilities: Business engagement and product strategy · Lead discovery with Business Owners; translate priorities into product visions, value cases, roadmaps, backlogs, and measurable success criteria. · Maintain alignment on priorities, scope, investment, sequencing, risks, dependencies, and trade-offs. · Communicate strategy, delivery progress, key decisions, and realized value to business and technical stakeholders. Technical delivery leadership & innovation · Identify, evaluate, and scale innovative data, analytics, and AI-enabled capabilities that improve decision-making, productivity, automation, and business outcomes. · Lead the delivery of reusable data products that enable governed, discoverable, high-quality, and scalable use of enterprise data. · Partner with EDSE and AIN Engineering teams to evaluate and apply agentic data-engineering capabilities, including automated data pipeline development, data-quality monitoring, metadata and documentation generation, observability, and issue resolution, where appropriate. · Balance innovation with enterprise standards for architecture, security, privacy, compliance, reliability, cost, and operational support. Value realization and lifecycle management · Define and track adoption, operational, delivery, and business-value metrics for assigned initiatives. · Lead post-launch adoption, support, enhancement prioritization, and lifecycle management. · Promote reuse of EDSE platforms, shared data products, and engineering patterns to enable scalable enterprise delivery. What we expect of you We are all different, yet we all use our unique contributions to serve patients. The professional we seek is an individual with these qualifications. Basic Qualifications: Doctorate degree and 2 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field OR Master’s degree and 6 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field OR Bachelor’s degree and 8 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field OR Associate’s degree and 10 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field OR High school diploma / GED and 12 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field In addition to meeting at least one of the above requirements, you must have a minimum of 2 years’ experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation of resources. Your managerial experience may run concurrently with the required technical experience referenced above. Required Qualifications: · Experience delivering data, analytics, reporting, or digital solutions in the life sciences industry, working with large global teams · Demonstrated experience leading cross-functional data and analytics initiatives from discovery through production delivery, adoption, and ongoing support. · Demonstrated experience delivering solutions using Databricks, AWS, Power BI, and related data, analytics, cloud, integration, or visualization technologies. · Ability to translate business needs into product requirements, delivery plans, measurable outcomes, and production-ready solutions. · Strong stakeholder-management, communication, facilitation, and decision-making skills. Preferred Qualifications: · Experience leading enterprise-scale data, analytics, reporting, AI, or digital-product initiatives in a complex, matrixed organization. · Experience with Agile or scaled Agile delivery practices, including product roadmaps, backlog management, PI planning, release planning, and continuous improvement. · Experience developing or delivering reusable enterprise data products, including governed datasets, data pipelines, semantic models, APIs, or analytics products. · Experience with AI-enabled or agentic data-engineering capabilities, such as intelligent pipeline automation, data-quality remediation, metadata generation, data observability, or AI-assisted engineering workflows. · Knowledge of GxP, validation, data governance, privacy, security, and regulatory expectations relevant to life sciences data and analytics. · Ability to manage competing priorities, navigate ambiguity, make transparent trade-offs, and drive decisions to closure. What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journ